20 April 2019
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Int J Med Sci 2019; 16(1):93-105. doi:10.7150/ijms.29560
Deduction of Novel Genes Potentially Involved in Upper Tract Urothelial Carcinoma Using Next-Generation Sequencing and Bioinformatics Approaches
1. Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
Upper tract urothelial carcinoma (UTUC) is a relatively uncommon cancer worldwide, however it accounts for approximately 30% of urothelial cancer in the Taiwanese population. The aim of the current study is to identify differential molecular signatures and novel miRNA regulations in UTUC, using next-generation sequencing and bioinformatics approaches. Two pairs of UTUC tumor and non-tumor tissues were collected during surgical resection, and RNAs extracted for deep sequencing. There were 317 differentially expressed genes identified in UTUC tissues, and the systematic bioinformatics analyses indicated dysregulated genes were enriched in biological processes related to aberration in cell cycle and matrisome-related genes. Additionally, 15 candidate genes with potential miRNA-mRNA interactions were identified. Using the clinical outcome prediction database, low expression of SLIT3 was found to be a prognostic predictor of poor survival in urothelial cancer, and a novel miRNA, miR-34a-5p, was a potential regulator of SLIT3, which may infer the potential role of miR-34a-5p-SLIT3 regulation in the altered tumor microenvironment in UTUC. Our findings suggested novel miRNA target with SLIT3 regulation exerts potential prognostic value in UTUC, and future investigation is necessary to explore the role of SLIT3 in the tumor development and progression of UTUC.
Keywords: upper tract urothelial carcinoma, cell cycle, matrisome, next-generation sequencing, bioinformatics
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How to cite this article:
Lee HY, Chen YJ, Li CC, Li WM, Hsu YL, Yeh HC, Ke HL, Huang CN, Li CF, Wu WJ, Kuo PL. Deduction of Novel Genes Potentially Involved in Upper Tract Urothelial Carcinoma Using Next-Generation Sequencing and Bioinformatics Approaches. Int J Med Sci 2019; 16(1):93-105. doi:10.7150/ijms.29560. Available from http://www.medsci.org/v16p0093.htm